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Stephan Thaler
Stephan Thaler
Valence Labs
Preverjeni e-poštni naslov na tum.de
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Leto
Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting
S Thaler, J Zavadlav
Nature communications 12 (1), 6884, 2021
682021
Sparse identification of truncation errors
S Thaler, L Paehler, NA Adams
Journal of Computational Physics 397, 108851, 2019
372019
Deep coarse-grained potentials via relative entropy minimization
S Thaler, M Stupp, J Zavadlav
The Journal of Chemical Physics 157 (24), 2022
262022
Scalable Bayesian uncertainty quantification for neural network potentials: promise and pitfalls
S Thaler, G Doehner, J Zavadlav
Journal of Chemical Theory and Computation 19 (14), 4520-4532, 2023
182023
Back-mapping augmented adaptive resolution simulation
S Thaler, M Praprotnik, J Zavadlav
The Journal of Chemical Physics 153 (16), 2020
112020
Active learning graph neural networks for partial charge prediction of metal-organic frameworks via dropout Monte Carlo
S Thaler, F Mayr, S Thomas, A Gagliardi, J Zavadlav
npj Computational Materials 10 (1), 86, 2024
42024
chemtrain: Learning deep potential models via automatic differentiation and statistical physics
P Fuchs, S Thaler, S Röcken, J Zavadlav
Computer Physics Communications, 109512, 2025
22025
JaxSGMC: Modular stochastic gradient MCMC in JAX
S Thaler, P Fuchs, A Cukarska, J Zavadlav
SoftwareX 26, 101722, 2024
22024
Data Driven Modeling of the Laminar Flame Response Using Universal Differential Equations
G Doehner, CF Silva, S Thaler, J Zavadlav, W Polifke
TU München München, 2023
22023
Uncertainty Quantification for Molecular Models via Stochastic Gradient MCMC
S Thaler, J Zavadlav
10th Vienna Conference on Mathematical Modelling, 19-20, 2022
22022
OpenQDC: Open Quantum Data Commons
C Gabellini, N Shenoy, S Thaler, S Canturk, D McNeela, D Beaini, ...
arXiv preprint arXiv:2411.19629, 2024
12024
Implicit Delta Learning of High Fidelity Neural Network Potentials
S Thaler, C Gabellini, N Shenoy, P Tossou
arXiv preprint arXiv:2412.06064, 2024
2024
ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation
M Hassan, N Shenoy, J Lee, H Stark, S Thaler, D Beaini
arXiv preprint arXiv:2410.22388, 2024
2024
Advances in Neural Network Potentials for Molecular Dynamics Simulations: Physics-Informed Training and Uncertainty Quantification
S Thaler
Technische Universität München, 2023
2023
Partial Charge Assignment to Metal Organic Frameworks through Active Learning
S Thaler, F Mayr, S Thomas, A Gagliardi, J Zavadlav
ARTEMIS 1st Plenary meeting, 2022
2022
Equivariant Flow Matching for Molecular Conformer Generation
M Hassan, N Shenoy, J Lee, H Stark, S Thaler, D Beaini
ICML 2024 Workshop on Structured Probabilistic Inference {\&} Generative …, 0
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